Food expenditure patterns in the Canadian Arctic show cause for concern for obesity and chronic disease.

Auteur(s) :
Sharma S., Pakseresht M., Lang R., Rittmueller S., Roache C., Sheehy T., Batal M., Corriveau A.
Date :
Avr, 2014
Source(s) :
The international journal of behavioral nutrition and physical activity. #11:1 p51
Adresse :
Aboriginal and Global Health Research Group, Department of Medicine, University of Alberta, 5-10 University Terrace, Edmonton, AB T6G 2?T4, Canada.

Sommaire de l'article

Little is understood about the economic factors that have influenced the nutrition transition from traditional to store-bought foods that are typically high in fat and sugar amongst people living in the Canadian Arctic. This study aims to determine the pattern of household food expenditure in the Canadian Arctic.

Local food prices were collected over 12 months in six communities in Nunavut and the Northwest Territories. Dietary intake data were collected from 441 adults using a validated quantitative food frequency questionnaire. Money spent on six food groups was calculated along with the cost of energy and selected nutrients per person.

Participants spent approximately 10% of total food expenditure on each of the food groups of fruit/vegetables, grains and potatoes, and dairy, 17% on traditional meats (e.g. caribou, goose, char, and seal liver), and 20% on non-traditional meats (e.g. beef, pork, chicken, fish, and processed meats). Non-nutrient-dense foods (NNDF) accounted for 34% of food expenditure. Younger participants (<30 years) spent more on NNDF and less on traditional meats compared with the older age groups. Participants with higher levels of formal education spent more on fruit and vegetables and less on traditional meats, when compared with participants with lower levels of formal education.

Participants spent most household income on NNDF, a possible consequence of generation discrepancy between younger and older participants. The tendency toward NNDF, particularly among youth, should be addressed with an assessment of predictive factors and the development of targeted approaches to population-based interventions.

Source : Pubmed